How to Achieve High Data Quality in SAP MDG Solutions

Data quality is paramount in the implementation of SAP MDG (Master Data Governance) or SAP MDM (Master Data Management).

Your system is only as strong as your data. Therefore, data cleansing and data normalization are crucial steps to take before you actually launch SAP MDG/MDM implementation. We at IBA Group accumulated rich experience in ensuring that your data is ready and prepared for SAP MDG/MDM.

Examine Existing Master Data

Many companies make a decision to implement SAP MDG/SAP MDM when they already have arrays of legacy data. It comes down to a question of data confidence. Is your data structured, consistent, and contains unique, not duplicate records? If not, your system is not ready for SAP MDDM/MDG implementation.

Ultimately, the journey to data harmonization is well worth the effort and can result in significant improvements for companies willing to put in the effort.

Data preparation is key. SAP MDG is a data quality management solution. However, a situation often arises when, before launching SAP MDG into operation, it is required to bring in line with SAP quality criteria your legacy master data that afterwards will be maintained with the help of SAP MDG. So all data should be cleansed and normalized before SAP MDG implementation. Using multiple data sources can also present a problem.

Some of the common issues include:

• Mismatched figures and fields
• Corruption and validation issues
• Duplicate, inconsistent, and irrelevant records

Doing some legwork on the front end, you’ll ensure that your data is ready for the new system. These steps may include shoring up data integrity via testing or validating a sample or subset. Record-by-record comparison is more intensive but can also ensure data integrity. Finally, limited data migration may be an option when data is particularly lacking. It may seem like extra work in the short term, but the longer-term benefits of making the switch are significant.

Before you make the switch, running a master data readiness check is crucial to ensure what’s working and assist in the preparation process. The check will help make the path clear. All data must meet universal standards to ensure a smooth transition, mitigate errors, and simplify the process.

ECCMA and ECLASS: Standards for Data

As with many other fields and industries, there are universal standards in place for data quality. These standards ensure that all aspects of data are seamlessly transferred and understood, regardless of company, language, or technician.

Similar and related to ISO standards in engineering, the ECCMA and ECLASS data standards are global.

ECCMA: Founded in 1999, ECCMA is a nonprofit faction of the Code Management Association, developed by the UNSPC. ECCMA aims to create and disambiguate language used in master data in many factions of business, including data regarding organizations, goods, services, individuals, processes, locations, and regulations. ECCMA is the lead for ISO 22745 and ISO 8000 standards regarding data quality. ECCMA certifies Master Data Quality Managers, testifying that a person has basic knowledge about ISO 8000 and ISO 22745, and knows how the standards can be applied to produce and identify quality data.

ECLASS: Many goods and services are also covered by ECLASS standards. ECLASS is the worldwide data standard for the classification and unique description of product master data. ECLASS and ISO/IEC compliant standard is industry-specific, with 45,000 product classes and 19,000 properties organized into four classification levels. Each product or service is assigned an 8-digit code, creating a clear identifier that works beyond language, country, and industry constraints.

Both standards are used in data cleansing and help to disambiguate descriptions and create a universal language that can be used to identify data.

Choosing a Company with Experience

IBA Group has extensive experience in SAP MDG/MDM implementation in many different industries. We understand and apply international data cleansing and normalization standards, like eClass and ECCMA, to ensure the data is fully ready for SAP MDG/MDM implementation. With more than a decade of experience in SAP MDG/MDM and ECCMA-certified Master Data Quality Managers, we know how to clean master data for clients with large volumes of legacy data.

IBA also has exclusive proprietary MDG and MDM tools that we use to prepare data for SAP MDG implementation.

When companies go into the implementation process, there’s often a great deal of legacy data that requires cleanup. We recommend a testing period to check if the system is aligned and all data is clear, correct, and proofed before launching SAP MDG.

The IBA HOTD (Harmonized Ontological Technical Dictionary) solution improves the master data quality and prepares golden records for SAP MDM and MDG.

If you’re considering implementing SAP MDG/MDM, let us help you begin the process and set up your master data for a successful go-live.

For more information on data normalization, please read about Project Planning for SAP MDG Data Migration and Material Master Data Normalization and Golden Records for SAP MDG.